code: def uops_to_triton(function_name: str, uops: List[UOp]):
      local_size: List[int] = []
      depth = 1
      signatures, dims, bufs, kernel, valid = [], [], [], [], []  # type: ignore
  
      c: DefaultDict[str, int] = defaultdict(int)
      r: Dict[UOp, str] = {}
  
      def ssa(u, prefix="t"):
          nonlocal c, r
          c[prefix] += 1
          r[u] = f"{prefix}{c[prefix]-1}"
          return r[u]
  
      child_count: DefaultDict[UOp, int] = defaultdict(int)
      for ru in uops:
          for v in ru.vin:
              child_count[v] += 1
  
      def kk(s):
          kernel.append("  " * depth + s)
  
      code_for_op: Final[Dict[Op, Callable]] = {
          UnaryOps.EXP2: lambda x, dtype,: f"tl.math.exp2({x})",
          UnaryOps.LOG2: lambda x, dtype,: f"tl.math.log2({x})",
          UnaryOps.SIN: lambda x, dtype: f"tl.sin({x})",
          UnaryOps.SQRT: lambda x, dtype: f"tl.sqrt({x})",
          UnaryOps.NEG: lambda x, dtype: f"-{x}"
          if dtype != dtypes.bool
          else f"tl.where({x}, 0, 1)",
          BinaryOps.ADD: lambda x, y, dtype: f"({x}+{y})",
          BinaryOps.SUB: lambda x, y,: f"({x}-{y})",
          BinaryOps.MUL: lambda x, y, dtype: f"({x}*{y})",
          BinaryOps.DIV: lambda x, y,: f"({x}/{y})"
          if y != "0.0"
          else f"{x}*tl.where({x}==0.0, float('nan'), float('inf'))",
          BinaryOps.MAX: lambda x, y, dtype: f"tl.maximum({x},{y})",
          BinaryOps.CMPLT: lambda x, y, dtype: f"({x}<{y})",
          BinaryOps.MOD: lambda x, y, dtype: f"tl.abs({x})%tl.abs({y})*tl.where({x}<0,-1,1)",
          TernaryOps.MULACC: lambda x, y, z, dtype: f"(({x}*{y})+{z})",
          TernaryOps.WHERE: lambda x, y, z, dtype: f"tl.where({x},{y},{z})",
      }
  
      def int_div(x, y):
          return (
              f"({x}//{y})"
              if y != "0"
              else f"{x}*tl.where({x}==0, float('nan'), float('inf'))"
          )
  
      for u in uops:
          uop, dtype, vin, args = u.uop, u.dtype, u.vin, u.arg
          if uop == UOps.LOOP:
              kk(
                  f"for {ssa(u, 'ridx')} in range({vin[0].arg}, {r[vin[1]]}):"
              )
              depth += 1
          elif uop == UOps.END:
              depth -= 1
          elif uop == UOps.ALU:
              assert dtype is not None
              val = code_for_op[args](*[r[x] for x in vin])
              if child_count[u] <= 1 or dtypes.is_int(dtype):
                  r[u] = (
                      int_div(*[r[x] for x in vin])
                      if args == BinaryOps.DIV and dtypes.is_int(dtype)
                      else val
                  )
              else:
                  kk(f"{ssa(u, 'alu')} = ({val})")
          elif uop == UOps.LOAD:
              assert dtype is not None
              if len(vin) == 2:
                  kk(
                      f"{ssa(u, 'val')} = {render_cast(f'tl.load({r[vin[0]]} + { fill_dims_for_idx(r[vin[1]], dims)}, mask = {render_valid(valid)})', dtype)}"
                  )
              else:
                  kk(
                      f"{ssa(u, 'val')} = {render_cast(f'tl.where({r[vin[2]]}, tl.load({r[vin[0]]}+{fill_dims_for_idx(r[vin[1]],dims)} , mask={render_valid(valid+[r[vin[2]]])}), 0.0)', dtype)}"
                  )
          elif uop == UOps.DEFINE_ACC:
              kk(
                  f"{ssa(u, 'acc')} = {define_scalar(local_size, dtype, args).replace('//', '/')}"
              )
          elif uop == UOps.CONST:
              r[u] = define_scalar([], dtype, args)
          elif uop == UOps.PHI:
              kk(f"{r[vin[0]]} = {r[vin[1]].replace('//', '/')}")
              r[u] = r[vin[0]]
          elif uop == UOps.STORE:
              assert not isinstance(
                  dtype, ImageDType
              ), "unimplemented: image store"
              kk(
                  f"{'if '+r[vin[3]]+': ' if len(vin)>3 else ''}tl.store({r[vin[0]]} + {r[vin[1]]}, {r[vin[2]].replace('//', '/')}, mask = {render_valid(valid)}) "
              )
          elif uop == UOps.DEFINE_GLOBAL:
              bufs.append(args)
              signatures.append(
                  "*"
                  if isinstance(dtype, PtrDType)
                  else "" + signature_dtypes[dtype]
              )
              r[u] = args
          elif uop == UOps.SPECIAL:
              dims.append(args[1])
              valid.append(f"{args[1]}<{get_max(args[2])}")
              if args[1].startswith("g"):
                  kk(
                      f"{args[1]} = tl.program_id({args[0]}) # {args[2]}"
                  )
              elif args[1].startswith("l"):
                  kk(
                      f"{args[1]} = tl.arange({0}, {next_power_of_2(args[2])})"
                  )
                  local_size.append(args[2])
              r[u] = args[1]
          elif uop == UOps.CAST and dtype is not None:
              r[u] = render_cast(
                  r[vin[0]], dtype, isinstance(args, tuple) and args[1]
              )
          else:
              raise NotImplementedError(f"unimplemented: {uop}")
  
      prg = (
          f"import triton\nimport triton.language as tl\ntl.core.TRITON_MAX_TENSOR_NUMEL = float('inf')\n@triton.jit\ndef {function_name}("
          + ",".join(bufs)
          + "):\n"
      )
      for i, line in enumerate(
          list(filter(lambda line: "tl.arange" in line, kernel))
      ):
          kernel[
              kernel.index(line)
          ] += f"[{', '.join([':' if i == j else 'None' for j in range(len(local_size))])}]"
      prg += "\n".join(kernel)
  
      acc_local_size = 1
      for x in local_size:
          acc_local_size *= next_power_of_2(x)
      local_size = [acc_local_size] + [1] * (len(local_size) - 1)
  
      if DEBUG >= 4:
          print(prg)
      getlines = linecache.getlines
      linecache.getlines = (
          lambda filename, module_globals=None: prg.splitlines(
              keepends=True
          )
          if "<triton>" == filename
          else getlines(filename, module_globals)
      )
      exec(
          compile(prg, "<triton>", "exec"), globals()
      )  # pylint: disable=W0122\
      compiled = triton_compile(
          globals()[function_name],
          signature=",".join(signatures),
          device_type="cuda",
          debug=False,
          cc=(35 if getenv("CUDACPU", 0) else None),
      )
      prg = remove_single_scalar_curly_braces(
          compiled.asm["ptx"]
          .split(".file")[0]
          .split(".visible .func")[0]
      )
      max_local_size = [
          int(x)
          for x in prg.split(".maxntid ")[1].split("\n")[0].split(", ")
      ]
      for i in range(len(local_size)):
          local_size[i] = min(local_size[i], max_local_size[i])
  
      return prg, {
          "shared": compiled.metadata["shared"],
          "local_size": local_size + [1] * (3 - len(local_size)),
      }
  
file_path: tinygrad/extra/backends/triton.py
imports: from typing import Dict, List, Final, Callable, DefaultDict
  from collections import defaultdict
  from tinygrad.ops import UnaryOps, BinaryOps, TernaryOps, Op
  from tinygrad.helpers import DType, PtrDType, dtypes, ImageDType, DEBUG, getenv
  from tinygrad.codegen.linearizer import UOp, UOps
  from triton.compiler import compile
  import linecache
  import math
  import re
label_desc: Use image node_id 9 for calling a global function with example usage: uops_to_triton(function_name, uops) and returns: prg,  dict, r, unknown